School of Engineering
Showing 251-300 of 329 Results
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Wendy Gu
Assistant Professor of Mechanical Engineering and, by courtesy, of Materials Science and Engineering
BioThe Gu Group studies the mechanical behavior of nanomaterials. We work at the intersection of solid mechanics, materials science and nano-chemistry. We research the unique properties of nanoscale metals, ceramics and nano-architected composites in order to design strong, tough and lightweight structural materials, materials for extreme environments, and mechanically-actuated sensors. Our experimental tools include nanoindentation, electron microscopy, and colloidal synthesis.
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Matthew Joseph Guck
Undergraduate, Computer Science
Undergraduate, Hasso Plattner Institute of DesignBioClass of 2026 President
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Nicholas Guesken
Postdoctoral Scholar, Materials Science and Engineering
BioNicholas is a postdoctoral research fellow in Prof. Mark Brongersma’s group at the Geballe Laboratory for Advanced Materials (GLAM), Stanford University. His research is supported by a science fellowship from the German National Academy of Science - Leopoldina. His research interests include nanophotonics, optoelectronics, plasmonics, photonic integration, quantum photonics, nonlinear optics, photon-emitter interfaces, emission enhancement of quantum emitters, active metasurfaces, and phase change materials.
Nicholas is an experimental condensed matter physicist. After obtaining Master's degrees in Physics (RWTH Aachen) and Nanotechnology (Sorbonne), Nicholas began his Ph.D. at Imperial College London. During his Ph.D., he focused on light-matter interaction on the nanoscale, hot-carrier photodetection, and hybrid photonic-plasmonic waveguides. His supervisors were Prof. Stefan Maier and Prof. Rupert Oulton. He completed his Ph.D. in 2020, for which he was awarded the Imperial College Solid State Physics Thesis Prize 2020 for the best thesis. Shortly after, he joined a startup company in Switzerland working on the development of high-speed optical interconnects.
In 2021, he was awarded the competitive Science Fellowship from the German National Academy of Science - Leopoldina, which has been supporting his research at Stanford. At Stanford University, he works on active solid-state optical interfaces with two main research directions: i) quantum emitter control in integrated photonic networks and ii) reconfigurable beam steering in phase change material-based metasurfaces. -
Carlos Ernesto Guestrin
Fortinet Founders Professor
BioCarlos Guestrin is a Professor in the Computer Science Department at Stanford University. His previous positions include the Amazon Professor of Machine Learning at the Computer Science & Engineering Department of the University of Washington, the Finmeccanica Associate Professor at Carnegie Mellon University, and the Senior Director of Machine Learning and AI at Apple, after the acquisition of Turi, Inc. (formerly GraphLab and Dato) — Carlos co-founded Turi, which developed a platform for developers and data scientist to build and deploy intelligent applications. He is a technical advisor for OctoML.ai. His team also released a number of popular open-source projects, including XGBoost, LIME, Apache TVM, MXNet, Turi Create, GraphLab/PowerGraph, SFrame, and GraphChi.
Carlos received the IJCAI Computers and Thought Award and the Presidential Early Career Award for Scientists and Engineers (PECASE). He is also a recipient of the ONR Young Investigator Award, NSF Career Award, Alfred P. Sloan Fellowship, and IBM Faculty Fellowship, and was named one of the 2008 ‘Brilliant 10’ by Popular Science Magazine. Carlos’ work received awards at a number of conferences and journals, including ACL, AISTATS, ICML, IPSN, JAIR, JWRPM, KDD, NeurIPS, UAI, and VLDB. He is a former member of the Information Sciences and Technology (ISAT) advisory group for DARPA. -
Leonidas Guibas
Paul Pigott Professor of Engineering and Professor, by courtesy, of Electrical Engineering
On Leave from 01/01/2025 To 03/31/2025Current Research and Scholarly InterestsGeometric and topological data analysis and machine learning. Algorithms for the joint analysis of collections of images, 3D models, or trajectories. 3D reconstruction.
